AI Performance & Automation Lead

About the Role:

Our organization operates on a governance framework — Steering Committee, Governance Council, Delivery/Working Groups, risk tiering, RACI, and a formal intake process — that exists to keep AI development safe, compliant, and well-prioritized. We're looking for an AI Governance & Performance Lead to own two closely related things: running that governance machinery day to day, and owning the KPI framework that proves the department's use cases are delivering value.

This is a process-and-measurement role, not a delivery-tracking one — the AI Program Manager owns whether things ship on time; you own whether they were vetted correctly on the way in, and whether anyone can prove they were worth building on the way out.

What You'll Do:

• Own and continuously improve the intake process, ensuring every new use case is captured, scoped, and risk-tiered consistently
• Run the operating cadence for the Steering Committee, Governance Council, and Delivery/Working Groups — agendas, materials, follow-through on decisions and action items
• Apply and maintain the risk-tiering framework, ensuring higher-risk use cases (data sensitivity, model risk, regulatory exposure) get appropriate scrutiny before build begins
• Maintain the RACI and governance documentation so accountability is clear and audit-ready at any point
• Define and own the enterprise AI KPI framework: adoption, business impact, model performance, and risk/compliance metrics, applied consistently across use cases
• Build and maintain portfolio-level performance reporting (in partnership with the Visualization & Full-Stack Developer for the technical build) that leadership can trust
• Push back on use case teams that want to redefine success metrics after the fact to justify a result, protecting the integrity of the measurement framework
• Support internal and external audit or compliance requests related to AI governance and model risk

Basic Qualifications:

• Bachelor's degree
• Minimum 5 years in governance, risk, compliance, program operations, or a related field, ideally with exposure to AI/ML or data governance specifically
• Experience designing or operating a formal review/approval process in a large, matrixed enterprise
• Strong analytical skills and comfort defining and tracking KPIs; experience building or overseeing a metrics/reporting framework
• Process-design mindset — you can tell the difference between rigor that protects the company and bureaucracy that just adds friction, and you design for the former
• Excellent documentation discipline and comfort operating in a way that would hold up to an audit
• Confident enough to push back on stakeholders — including senior ones — who want to skip a step or redefine success after the fact

Preferred Qualifications:

• Minimum 7 years in governance, risk, compliance, program operations, or a related field, with direct AI/ML or data governance experience
• Relevant risk/governance certification (e.g., CRISC, CISA) or an advanced degree
• Experience with AI-specific governance frameworks (NIST AI RMF, ISO 42001, or similar)
• Prior automotive or manufacturing enterprise risk/compliance experience
• Experience building enterprise AI KPI frameworks from scratch

Success in the First 12 Months Looks Like:

• A governance cadence that runs predictably, with decisions documented and action items tracked to closure
• A KPI framework applied consistently across the portfolio, giving leadership a defensible answer to "is AI actually working here"